What problem does it solve? AI-generated code often suffers from over-engineering, excessive comments, deep nesting, and inconsistent naming, making it hard to maintain. This Skill enforces pragmatic coding standards so every code change is concise, direct, and solution-focused. ## Core Features & Use Cases - Coding Standards Enforcement: Applies SRP, DRY, KISS, YAGNI, and Boy Scout principles with concrete naming, function size, and structure rules. - Anti-Pattern Detection: Flags common mistakes like god functions, magic numbers, unnecessary helpers, and obvious comments, with fixes for each. - Dependency-Aware Editing: Requires checking imports, dependents, and tests before modifying any file, preventing broken references. - Verification Workflow: Mandates self-checks and per-agent validation scripts with a read-summarize-ask output handling protocol. - Use Case: When an AI agent implements a feature or fixes a bug, this Skill ensures the resulting code is small, well-named, free of dead abstractions, and that all dependent files are updated in the same task. ## Quick Start Apply the clean-code standards to review and refactor the code you just wrote, keeping functions small and removing unnecessary comments.
